PROJECT SUMMARY/ ABSTRACT Despite promising initial responses, most BRAF-mutant melanoma patients eventually fail on BRAF inhibitor therapy. The task of understanding therapeutic escape and dissemination is complicated further by the countless number of resistance mechanisms identified so far and the realization that multiple cellular phenotypes may exists within a single genotype. The roles of intra-tumoral heterogeneity in progression and drug resistance are poorly understood, and we submit that strategies tackling this diversity are needed for durable therapeutic responses in patients. We hypothesize that: (i) drug-induced tumor cell phenotypic heterogeneity is driven by the development of inter-dependent and cooperative metabolic niches that promote tumor dissemination and affect the response to therapeutics; and (ii) therapeutic approaches that exploit intra- clonal metabolic competition will give more durable responses in melanoma patients. We will define the metabolic landscape of OXPHOS-dependent and glycolysis-dependent subpopulations in cell culture, xenografts, patient-derived xenografts (PDX) and patient specimens using single-cell RNAseq, global metabolomics and targeted expression panels. We will test how OXPHOS-dependent and glycolysis- dependent subpopulations cooperate to drive metastasis and define the drug sensitivities of the individual subpopulations in vitro and in xenografts and PDXs. We will test if disrupting either OXPHOS or glycolysis, pharmacologically or through gene expression targeting, shapes the metastatic potential or the emergence and heterogeneity of drug resistant subpopulations. We will devise a mathematical model to define optimal, evolutionary-informed dosing of BRAF/MEK plus metabolic inhibitor combinations that impair clonal cooperation and maximize duration of the therapeutic response. These models will be validated in vitro and in PDX models. The K99/R00 award would allow the candidate to conduct the proposed studies under the continued guidance of their primary mentor, Dr. John Cleveland, together with a panel of co-mentors who are renowned experts in melanoma biology, PDX modeling, cancer evolution, metabolism, and statistical and computational approaches to systems-wide large-scale data set analysis. During the K99 phase, the candidate will further develop their knowledge in melanoma metabolism and evolutionary biology, as well as their technical abilities in mass-spectrometry-based metabolomics, advanced computational biology, bioinformatics and biostatistics. With the help of their committee and various seminars, courses and workshops, the candidate will become a stronger scientist, manager, grant writer and mentor, all skills necessary to be an independent investigator. Overall, the proposed work will provide the rationale for therapeutic approaches that exploit intra-clonal metabolic competition to give more durable responses in melanoma patients, as well as a timely career transition for a candidate with strong potential to be a successful independent investigator.